Conference
Knowledge Base Completion for Long-Tail Entities
| العنوان: | Knowledge Base Completion for Long-Tail Entities |
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| المؤلفون: | Lihu Chen, Simon Razniewski, Gerhard Weikum |
| بيانات النشر: | Zenodo |
| سنة النشر: | 2023 |
| المجموعة: | Zenodo |
| الوصف: | We developed a new dataset with an emphasis on the long-tail challenge, called MALT (for “Multi-token, Ambiguous, Long-Tailed facts”). The dataset contains 65.3% triple facts where the O entity is a multi-word phrase, and 58.6% ambiguous facts where the S or O entities share identical alias names in Wikidata. For example, the two ambiguous entities ,“Birmingham, West Midlands (Q2256)” and “Birmingham, Alabama (Q79867)”, have the same Label value “BirminghamBirmingham”. In total, 87.0% of the sample facts have entities in the long tail, where we define long-tail entities to have at most 13 Wikidata triples. |
| نوع الوثيقة: | conference object |
| اللغة: | unknown |
| Relation: | https://doi.org/10.5281/zenodo.8092561; https://doi.org/10.5281/zenodo.8097738; oai:zenodo.org:8097738 |
| DOI: | 10.5281/zenodo.8097738 |
| الاتاحة: | https://doi.org/10.5281/zenodo.8097738 |
| Rights: | info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode |
| رقم الانضمام: | edsbas.F325D9CE |
| قاعدة البيانات: | BASE |
| DOI: | 10.5281/zenodo.8097738 |
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